ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Glycogen synthase 1 (GYS1) is the rate-limiting enzyme responsible for glycogen synthesis in skeletal muscle, heart, brain, and other extrahepatic tissues, playing a central role in systemic energy homeostasis. The human GYS1 gene maps to chromosome 19q13.33, comprises 16 exons, and encodes a 737-amino-acid polypeptide that is highly conserved across mammals. GYS1 activity is subject to multilayered and precisely coordinated regulation. At the transcriptional level, the GYS1 promoter contains a hypoxia response element (HRE) that mediates HIF-1α-dependent induction under low-oxygen conditions, as well as a muscle-specific enhancer harboring MEF2 and MyoD binding sites that confers tissue-restricted expression. At the post-translational level, a hierarchical phosphorylation cascade serves as the primary activity switch: glycogen synthase kinase 3β (GSK3β) sequentially phosphorylates four C-terminal serine residues following casein kinase II priming, while protein kinase A (PKA) and AMP-activated protein kinase (AMPK) provide parallel inhibitory inputs at both N- and C-terminal sites. Dephosphorylation and reactivation are mediated by protein phosphatase 1 (PP1) through tissue-specific glycogen-targeting regulatory subunits such as PPP1R3A and PPP1R3B, which anchor PP1 to glycogen particles and direct its activity toward GYS1. The allosteric activator glucose-6-phosphate (G6P) binds at the dimer interface, simultaneously enhancing catalytic efficiency and promoting dephosphorylation susceptibility, thereby establishing a feed-forward activation loop that couples substrate availability to glycogen synthesis. Beyond phosphorylation, GYS1 is regulated by ubiquitination (mediated by the E3 ligase PJA1), acetylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification, and SUMOylation, which collectively modulate protein stability, subcellular localization, and protein-protein interactions. Epigenetic mechanisms, including CpG island methylation and histone acetylation dynamics, govern chromatin accessibility at the GYS1 locus, while muscle-specific microRNAs such as miR-1 and miR-206 fine-tune GYS1 expression at the post-transcriptional level. Dysregulation of GYS1 has been identified as a central pathogenic driver in a spectrum of human diseases. In inherited glycogen storage disorders—including Lafora disease, adult polyglucosan body disease (APBD), and Pompe disease—loss of upstream regulatory control leads to GYS1 hyperactivation and the accumulation of structurally abnormal or excessive glycogen, resulting in progressive neurodegeneration, myopathy, and multiorgan dysfunction. In type 2 diabetes mellitus (T2DM), impaired insulin signaling through the PI3K-AKT-GSK3β axis maintains GYS1 in a hyperphosphorylated inactive state in skeletal muscle, compromising postprandial glucose disposal and exacerbating hyperglycemia. In oncology, GYS1 exhibits context-dependent roles across multiple cancer types. In hepatocellular carcinoma, FMO2⁺ cancer-associated fibroblasts stabilize GYS1 by competitively inhibiting PJA1-mediated ubiquitination, and stabilized GYS1 subsequently activates NF‑κB/CCL19 signaling to promote tertiary lymphoid structure formation and enhance anti-PD-1 immunotherapy responsiveness. In clear cell renal cell carcinoma, GYS1 promotes tumor progression through non-canonical NF‑κB pathway activation via the scaffold protein RPS27A. In triple-negative breast cancer, GYS1 has been identified as a trigger of disulfidptosis and an activator of NF-κB signaling through non-enzymatic facilitation of IκBα degradation. In colorectal cancer, mitochondrial fission deficiency drives AMPK-dependent GYS1 upregulation and glycogen accumulation as a compensatory survival mechanism, while in cervical cancer, GYS1-maintained glycogen reserves fuel the pentose phosphate pathway to generate NADPH for ROS clearance, thereby conferring cisplatin resistance in cancer stem cells. Therapeutic strategies targeting GYS1 have gained substantial momentum across these disease contexts. For glycogen storage disorders, antisense oligonucleotides, small interfering RNAs (e.g., ABX1100), and small-molecule inhibitors (e.g., MZ-101) have demonstrated preclinical and early clinical efficacy in reducing pathological glycogen accumulation. For T2DM, pharmacological activation of GYS1 through GSK3β inhibition or enhancement of PP1-mediated dephosphorylation is being explored to restore insulin-stimulated glycogen synthesis. In cancer, GYS1-directed interventions—including targeted silencing to sensitize tumors to chemotherapy and immune microenvironment modulation to enhance immunotherapy—represent emerging precision oncology approaches. This review provides a comprehensive and integrated account of GYS1 gene structure, tissue-specific distribution, regulatory networks, and pathogenic roles in metabolic disorders and malignancies, with the aim of establishing a theoretical framework for the development of GYS1-targeted precision therapies.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Objective:To investigate the basic information of diagnostic and therapeutic nuclear medicine resources and practices in Henan province in 2022, and to assess the equity of their distribution, and to compare them with the 1998 survey result, so as to provide the reference for the allocation of nuclear medicine resources in Henan province.Methods:On-site investigations were conducted on medical institutions in Henan province that carry out diagnostic and therapeutic nuclear medicine practices. By using a combination of Lorenz curve, Gini coefficient and Theil index, the fairness of nuclear medicine resources and practices were assessed based on population distribution in Henan province in 1998 and 2022.Results:In 2022, there were 54 medical institutions in Henan province that carried out diagnostic and therapeutic nuclear medicine practices, with 67 items of nuclear medicine imaging and supporting equipment, and 690 nuclear medicine staff members involved. A total of 200 938 diagnostic clinical nuclear medicine imaging practices were performed throughout the year, with a diagnostic frequency of 2.04 per 1 000 population. Various types of therapeutic nuclear medicine practices were performed on 29 044 individuals, with a frequency of 0.29 per 1 000 population. The Gini coefficients for the distribution of diagnostic nuclear medicine practices, nuclear medicine staff, and practice frequency based on population distribution in Henan province in 1998 were 0.489, 0.505, and 0.526, respectively, and the Theil indices were 0.091 8, 0.172 1, and 0.139 7, respectively. The Gini coefficients for the distribution of nuclear diagnostic medicine equipment, nuclear medicine staff, and practice frequency based on population distribution in Henan province in 2022 were 0.244, 0.246, and 0.363, respectively, and the Theil indices were 0.086 8, 0.145 3, and 0.159 9, respectively.Conclusions:While clinical nuclear medicine in Henan province is rapidly developing, the distribution of various types of nuclear medicine resources and practices is becoming increasingly balanced. However, there still exists a certain degree of imbalance. Additionally, this also demonstrates a correlation between the resource distribution and regional economic development. The rationality of resource allocation needs further optimization.

This study investigates the expression pattern and functional significance of EF-hand domain-containing protein 2 (EFHD2) in hepatocellular carcinoma (HCC), with particular focus on its regulatory effects on tumor proliferation, migration, and invasion. Cellular experimental study was completed from June 2024 to January 2025 in the Basic Laboratory of the General Hospital of Southern Theater Command. TCGA database to determine EFHD2 expression and its clinicopathological correlations. GSCA database to assess methylation patterns and immune infiltration. Model of transient overexpression and knockdown of EFHD2 was constructed in hepatocellular carcinoma cells Hep3B, then RT-qPCR and Western blot were applied to verify the transfection efficiency. CCK-8 and colony formation assays for proliferation assessment, Transwell chambers for migration/invasion quantification. Protein-protein interaction networks were constructed via STRING, followed by GO/KEGG enrichment analysis. Statistical analysis was performed using the two independent samples t-test. The results showed that EFHD2 demonstrated significant upregulation in HCC tissues versus normal controls ( P<0.05). Elevated EFHD2 expression correlated with advanced clinical stage ( P<0.05) and poor differentiation ( P<0.05). In the CCK-8 assay, the EFHD2 overexpression group demonstrated significantly higher cell viability than the control group, as evidenced by 450 nm relative absorbance values on Day 1 (0.529±0.019 vs. 0.515±0.016, F=0.041, P=0.320), Day 2 (1.356±0.019 vs. 1.094±0.042, F=3.833, P<0.001), Day 3 (2.817±0.049 vs. 2.143±0.124, F=3.833, P<0.001), and Day 4 (3.848±0.015 vs. 3.430±0.021, F=0.469, P<0.001). The EFHD2 knockdown group showed reduced cell viability compared to controls: Day 1 (0.541±0.020 vs. 0.552±0.015, F=0.098, P=0.423), Day 2 (1.154±0.009 vs. 1.326±0.029, F=2.485, P<0.001), Day 3 (2.453±0.041 vs. 2.653±0.031, F=0.479, P<0.001), and Day 4 (3.685±0.038 vs. 3.836±0.021, F=6.804, P<0.001). In colony formation assays, the overexpression group displayed a significant increase in colony numbers (254.667±23.861 vs. 186.000±16.703, F=0.865, P=0.015), whereas the knockdown group exhibited decreased colony formation (229.000±24.637 vs. 306.667±36.501, F=0.988, P=0.038). In Transwell assays, the EFHD2 overexpression group revealed enhanced migratory capacity [ (605.000±72.670) cells vs. (472.667±28.095) cells, F=2.462, P=0.042] and invasive potential [(767.333±21.221) cells vs. (414.333±16.623) cells, F=0.331, P<0.001]. The knockdown group showed attenuated migration [(311.000±71.084) cells vs. (479.667±50.846) cells, F=0.718, P=0.029] and invasion [(247.667±48.263) cells vs. (345.667±32.130) cells, F=0.727, P=0.043] compared to controls. The network of EFHD2-interacting proteins was further constructed by the STRING database, and the GO and KEGG analysis were used to perform bioinformatics analysis reveal that EFHD2 is mainly involved in actin cytoskeleton regulation. In conclusion, EFHD2 is highly expressed in HCC and is involved in the process of proliferation, migration and invasion of HCC.

Objective:To investigate the differences between high-frequency ultrasound-guided manual detorsion combined with surgery(MD+S)and surgery alone in the treatment of testicular torsion,and to provide some new evidence for the timely diagno-sis and treatment of the disease.Methods:We retrospectively analyzed the clinical data on 134 cases of unilateral testicular torsion within 48 hours treated in our hospital by MD+S or by surgery alone from January 2015 to May 2022.We statistically analyzed the age distribution,and duration and degrees of testicular torsion,followed by comparison between the two groups.Results:In the 134 ca-ses,the median age of onset was 15(13-19)years old,the median onset-to-visit time was 15(8-25)hours,and the median de-gree of torsion was 360°(180°-1080°).Of the total number of patients,21 underwent testicular excision and the other 113 were treated with the testis preserved,with no statistically significant difference in age distribution between the two groups(P＞0.05),and a higher rate of testis resection in those with longer duration and greater angle of torsion(P＜0.05).Totally,33 of the patients were assigned to the MD+S group and 101 to the surgery alone group.According to the actual clinical conditions and excluding those with torsion time longer than 24 hours and torsion angle greater than 720 °,28 of the patients underwent ultrasound-guided MD+S(with 1 case of testis resection,3.6％),and 68 received surgery alone(with 7 cases of testis resection,10.3％).The rate of testis resection was higher in the surgery alone than that in the MD+S group,but with no statistically significant difference between the two groups(P＞0.05),which was considered to be related to the small sample size in this study.Conclusion:The popularization of testicular torsion knowledge can shorten the onset-to-visit time,and reasonable manual detorsion before emergency surgery can reduce the rate of testis resection.

Objective To elucidate the functional role and underlying mechanisms of the ribosome biogenesis factor BMS1 in neuroblastoma(NB)cellular proliferation.Methods We utilized the R2 genomics analysis and visualization platform to analyze the correlation between BMS1 expression levels and clinical characteristics of NB children.The BMS1 mRNA level in three human neuroblastoma cells SK-N-BE(2),BE(2)-C,IMR-32 and two normal cells hTERT RPE-1,IMR-90 was detected by real-time quantitative polymerase chain reaction(RT-qPCR).Two distinct small interfering RNA(siRNA)sequences were used to target BMS1 mRNA in NB cells SK-N-BE(2)and BE(2)-C,with normal cells hTERT RPE-1 serving as controls.We used RT-qPCR to quantify the mRNA levels of BMS1 and two key neuroblastoma-associated molecules(MYCN and p53).After transfection with siRNA,cellular proliferation was detected by various experimental approaches:crystal violet staining,real-time cell analysis(RTCA),colony-forming unit assay and immunofluorescence.Results By analyzing two independent neuroblastoma clinical cohorts(GSE85047/NRC-283 and Westermann-144 datasets),it was found that the BMS1 mRNA level in MYCN-amplified NB was significantly higher than that in MYCN-non-amplified NB(P<0.05).Furthermore,the overall survival rate of NB children in the BMS1 high-expression group was decreased(P<0.05).Consistent with these clinical observations,the BMS1 mRNA level in NB cells SK-N-BE(2),BE(2)-C and IMR-32 was significantly higher than that in normal cells hTERT RPE-1,IMR-90(P<0.05).The targeted transient knockdown of BMS1 in NB cell lines SK-N-BE(2)and BE(2)-C resulted in decreased intracellular MYCN mRNA expression levels(P<0.05),significantly reduced cell proliferation capacity and colony-forming ability(P<0.05).Immunofluorescence revealed that the expression of Ki-67,a proliferation marker,was decreased(P<0.05).At the molecular level,RT-qPCR showed that the p53 mRNA level was significantly elevated in the BMS1-knockdown groups(si BMS1-1#and si BMS1-2#)compared with the control group(P<0.05).However,transient knockdown of BMS1 had no significant impact on the proliferative capacity of normal cells hTERT RPE-1.Conclusion BMS1 expression was up-regulated in MYCN-amplified NB and negatively correlated with the prognosis of the NB children.Mechanistically,interfering with BMS1 expression may transcriptionally activate p53 in NB cells,thereby inhibiting their proliferative ability,while having minimal impact on normal cells growth kinetics.These findings suggest that BMS1 serves as an important proliferation driver in NB and is expected to be a promising therapeutic target for NB children,particularly MYCN-amplified pediatric patients.

The high cost,high loss and high increase of test reagents are the difficulties in the management of hospital health consumables.The case hospital to industry and financial integration mechanism,process reengineering theory as the basis for practicing reagent whole process cost control.Through effective data governance,a comparison relationship is established between revenue and expenditure.The standard cost method is utilized to identify potential areas for reduction,allowing for the determination of cost control targets.Subsequently,design process reengineering scheme and steps,so as to create a new reagent cost control process where hospital and enterprises work together,and a new method of cost settlement of fixed ratio of income and expenditure.Through dual-directional performance appraisal,the management results are solidified,enabling dual control and reduction of procurement costs and usage expenses.This approach enhances inspection efficiency,quality,and service while effectively mitigating associated risks.

AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.